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ORCIDMartine Ceberio
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- affiliation: University of Texas at El Paso, USA
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2020 – today
- 2024
[j17]Martine Ceberio, Christoph Quirin Lauter, Vladik Kreinovich:
Just-in-Accuracy: Mobile Approach to Uncertainty. J. Mobile Multimedia 20(3): 665-678 (2024)- 2023
- [j16]Phuoc Nguyen Kim, Jonatan M. Contreras, Martine Ceberio, Nguyen Ngoc Thach:
Economic and Financial Applications of Benford's Law: from Traditional Use in Audits to Help in Deep Learning. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 31(Supplement-2): 197-207 (2023) - [c59]Martine Ceberio, Vladik Kreinovich, Olga Kosheleva, Günter Mayer:
Complex-Valued Interval Computations are NP-Hard Even for Single Use Expressions. NAFIPS 2023: 246-257 - [c58]Martine Ceberio, Vladik Kreinovich, Olga Kosheleva, Lev Ginzburg:
Faster Algorithms for Estimating the Mean of a Quadratic Expression Under Uncertainty. NAFIPS 2023: 290-300 - [c57]Palvi Aggarwal, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
How People Make Decisions Based on Prior Experience: Formulas of Instance-Based Learning Theory (IBLT) Follow from Scale Invariance. NAFIPS 2023: 312-319 - [c56]Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Integrity First, Service Before Self, and Excellence: Core Values of US Air Force Naturally Follow from Decision Theory. NAFIPS 2023: 320-324 - [c55]Lehel Dénes-Fazakas
, László Szilágyi, György Eigner, Olga Kosheleva, Martine Ceberio, Vladik Kreinovich:
Which Activation Function Works Best for Training Artificial Pancreas: Empirical Fact and Its Theoretical Explanation. SSCI 2023: 496-500 - [c54]Orsolya Csiszár, Gábor Csiszár, Olga Kosheleva, Martine Ceberio, Vladik Kreinovich:
Why Fuzzy Control Is Often More Robust (and Smoother): A Theoretical Explanation. SSCI 2023: 501-505 - [p37]Martine Ceberio, Christian Servin, Olga Kosheleva, Vladik Kreinovich:
How to Best Write Research Papers: Basic English? Sophisticated English? Decision Making Under Uncertainty and Constraints 2023: 75-80 - [p36]Julio C. Urenda, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Why Homogeneous Membranes Lead to Optimal Water Desalination: A Possible Explanation. Decision Making Under Uncertainty and Constraints 2023: 89-92 - [p35]Marina Tuyako Mizukoshi, Weldon A. Lodwick, Martine Ceberio, Vladik Kreinovich:
Which Interval-Valued Alternatives Are Possibly Optimal if We Use Hurwicz Criterion. Uncertainty, Constraints, and Decision Making 2023: 99-104 - [p34]Salvador Robles Herrera, Martine Ceberio, Vladik Kreinovich:
How to Get the Most Accurate Measurement-Based Estimates. Uncertainty, Constraints, and Decision Making 2023: 165-175 - [p33]Jonatan M. Contreras, Martine Ceberio, Vladik Kreinovich:
One More Physics-Based Explanation for Rectified Linear Neurons. Uncertainty, Constraints, and Decision Making 2023: 195-198 - [p32]Salvador Robles Herrera, Martine Ceberio, Vladik Kreinovich:
Why Model Order Reduction. Decision Making Under Uncertainty and Constraints 2023: 233-237 - [p31]Barnabás Bede, Marina Tuyako Mizukoshi, Martine Ceberio, Vladik Kreinovich, Weldon A. Lodwick:
Why Constraint Interval Arithmetic Techniques Work Well: A Theorem Explains Empirical Success. Uncertainty, Constraints, and Decision Making 2023: 313-322 - [p30]Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
How to Describe Relative Approximation Error? A New Justification for Gustafson's Logarithmic Expression. Uncertainty, Constraints, and Decision Making 2023: 323-327 - [p29]Martine Ceberio, Vladik Kreinovich:
Search Under Uncertainty Should be Randomized: A Lesson from the 2021 Nobel Prize in Medicine. Uncertainty, Constraints, and Decision Making 2023: 329-334 - [p28]Juan Carlos Figueroa García, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Estimating Skewness and Higher Central Moments of an Interval-Valued Fuzzy Set. Uncertainty, Constraints, and Decision Making 2023: 345-352 - [p27]Marina Tuyako Mizukoshi, Weldon A. Lodwick, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
An Argument in Favor of Piecewise-Constant Membership Functions. Uncertainty, Constraints, and Decision Making 2023: 377-386 - [p26]Marina Tuyako Mizukoshi, Weldon A. Lodwick, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Data Processing Under Fuzzy Uncertainty: Towards More Accurate Algorithms. Uncertainty, Constraints, and Decision Making 2023: 387-399 - [p25]Marina Tuyako Mizukoshi, Weldon A. Lodwick, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Epistemic Versus Aleatory: Case of Interval Uncertainty. Uncertainty, Constraints, and Decision Making 2023: 401-421 - [p24]Marina Tuyako Mizukoshi, Weldon A. Lodwick, Martine Ceberio, Vladik Kreinovich:
Standard Interval Computation Algorithm Is Not Inclusion-Monotonic: Examples. Uncertainty, Constraints, and Decision Making 2023: 423-440 - [p23]Salvador Robles Herrera, Martine Ceberio, Vladik Kreinovich:
Computing the Range of a Function-of-Few-Linear-Combinations Under Linear Constraints: A Feasible Algorithm. Uncertainty, Constraints, and Decision Making 2023: 451-457 - [p22]Leobardo Valera, Martine Ceberio, Vladik Kreinovich:
How to Select a Representative Sample for a Family of Functions? Uncertainty, Constraints, and Decision Making 2023: 459-466 - [e6]Martine Ceberio, Vladik Kreinovich:
Decision Making Under Uncertainty and Constraints - A Why-Book. Springer 2023, ISBN 978-3-031-16414-9 [contents] - [e5]Martine Ceberio, Vladik Kreinovich:
Uncertainty, Constraints, and Decision Making. Studies in Systems, Decision and Control 484, Springer 2023, ISBN 978-3-031-36393-1 [contents] - 2022
- [j15]Jonatan M. Contreras, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Why neural networks in the first place: a theoretical explanation. J. Intell. Fuzzy Syst. 43(6): 6947-6951 (2022) - [j14]Salvador Robles Herrera, Martine Ceberio, Vladik Kreinovich:
When is deep learning better and when is shallow learning better: qualitative analysis. Int. J. Parallel Emergent Distributed Syst. 37(5): 589-595 (2022) - [c53]Angel F. Garcia Contreras, Martine Ceberio:
Comparison of Higher-Order Approximations to Solve Dynamical Systems Using Interval Constraint Solving. WEA 2022: 3-18 - [e4]Barnabás Bede, Martine Ceberio, Martine De Cock, Vladik Kreinovich:
Fuzzy Information Processing 2020 - Proceedings of the 2020 Annual Conference of the North American Fuzzy Information Processing Society, NAFIPS 2020, Redmond, WA, USA, 20-22 August 2020. Advances in Intelligent Systems and Computing 1337, Springer 2022, ISBN 978-3-030-81560-8 [contents] - 2021
- [j13]Jonatan M. Contreras, Martine Ceberio, Vladik Kreinovich:
Why Dilated Convolutional Neural Networks: A Proof of Their Optimality. Entropy 23(6): 767 (2021) - [c52]Kelly Cohen, Laxman Bokati, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Why Fuzzy Techniques in Explainable AI? Which Fuzzy Techniques in Explainable AI? NAFIPS 2021: 74-78 - [c51]Sarah Hug, Martine Ceberio, Diego Aguirre, Scott King, Megan Thomas, Eliana Valenzuela, Tom Carter, Nayda Santiago:
Reflecting on Reflection: Integrating Critical Thinking into CS Teaching and Learning Practice. SIGCSE 2021: 1365 - [c50]Angel Fernando Garcia Contreras, Martine Ceberio:
Solving Dynamical Systems Using Windows of Sliding Subproblems. WEA 2021: 13-24 - 2020
- [j12]Ricardo Alvarez, Nick Sims, Christian Servin, Martine Ceberio, Vladik Kreinovich:
If Space-Time Is Discrete, It Could Be Possible to Solve NP-Complete Problems in Polynomial Time. Int. J. Unconv. Comput. 15(3): 193-218 (2020) - [c49]Vladik Kreinovich, Martine Ceberio, Olga Kosheleva:
White- and Black-Box Computing and Measurements Under Limited Resources: Cloud, High Performance, and Quantum Computing, and Two Case Studies - Robotic Boat and Hierarchical Covid Testing. ICTES 2020: 1-18 - [c48]Jonatan M. Contreras, Francisco Zapata, Olga Kosheleva, Vladik Kreinovich, Martine Ceberio:
Let Us Use Negative Examples in Regression-Type Problems Too. IV 2020: 296-300 - [c47]Ricardo Alvarez, Nick Sims, Christian Servin, Martine Ceberio, Vladik Kreinovich:
How to Reconcile Randomness with Physicists' Belief that Every Theory Is Approximate: Informal Knowledge Is Needed. NAFIPS 2020: 373-378 - [c46]Leobardo Valera, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Equations for Which Newton's Method Never Works: Pedagogical Examples. NAFIPS 2020: 413-419 - [c45]Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Optimal Search Under Constraints. NAFIPS 2020: 421-426 - [c44]Julio C. Urenda, Olga Kosheleva, Martine Ceberio, Vladik Kreinovich:
How Mathematics and Computing Can Help Fight the Pandemic: Two Pedagogical Examples. NAFIPS 2020: 439-442 - [p21]Christian Ayub, Martine Ceberio, Vladik Kreinovich:
How Quantum Computing Can Help with (Continuous) Optimization. Decision Making under Constraints 2020: 7-14 - [p20]Chitta Baral, Martine Ceberio, Vladik Kreinovich:
How Neural Networks (NN) Can (Hopefully) Learn Faster by Taking into Account Known Constraints. Decision Making under Constraints 2020: 15-20 - [p19]Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Italian Folk Multiplication Algorithm Is Indeed Better: It Is More Parallelizable. Decision Making under Constraints 2020: 59-64 - [p18]Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Reverse Mathematics Is Computable for Interval Computations. Decision Making under Constraints 2020: 65-70 - [p17]Angel F. Garcia Contreras, Martine Ceberio, Vladik Kreinovich:
Plans Are Worthless but Planning Is Everything: A Theoretical Explanation of Eisenhower's Observation. Decision Making under Constraints 2020: 93-98 - [p16]Angel F. Garcia Contreras, Martine Ceberio, Vladik Kreinovich:
Why Convex Optimization Is Ubiquitous and Why Pessimism Is Widely Spread. Decision Making under Constraints 2020: 99-104 - [p15]Olga Kosheleva, Martine Ceberio, Vladik Kreinovich:
Attraction-Repulsion Forces Between Biological Cells: A Theoretical Explanation of Empirical Formulas. Decision Making under Constraints 2020: 139-144 - [p14]Olga Kosheleva, Martine Ceberio, Vladik Kreinovich:
When We Know the Number of Local Maxima, Then We Can Compute All of Them. Decision Making under Constraints 2020: 145-151 - [p13]Leobardo Valera, Martine Ceberio, Vladik Kreinovich:
Why Burgers Equation: Symmetry-Based Approach. Decision Making under Constraints 2020: 211-216 - [e3]Martine Ceberio, Vladik Kreinovich:
Decision Making under Constraints. Springer 2020, ISBN 978-3-030-40813-8 [contents]
2010 – 2019
- 2019
- [c43]Martine Ceberio, Olga Kosheleva, Vladik Kreinovich, Luc Longpré:
Between Dog and Wolf: A Continuous Transition from Fuzzy to Probabilistic Estimates. FUZZ-IEEE 2019: 1-5 - [c42]Martine Ceberio, Olga Kosheleva, Vladik Kreinovich, Luc Longpré:
In Its Usual Formulation, Fuzzy Computation Is, In General, NP-Hard, But a More Realistic Formulation Can Make It Feasible. FUZZ-IEEE 2019: 1-6 - [c41]Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Can We Improve the Standard Algorithm of Interval Computation by Taking Almost Monotonicity into Account? IFSA/NAFIPS 2019: 767-778 - [c40]Leobardo Valera, Martine Ceberio, Vladik Kreinovich:
Derivation of Louisville-Bratu-Gelfand Equation from Shift- or Scale-Invariance. IFSA/NAFIPS 2019: 813-819 - [c39]Oscar Galindo, Christian Ayub, Martine Ceberio, Vladik Kreinovich:
Faster Quantum Alternative to Softmax Selection in Deep Learning and Deep Reinforcement Learning. SSCI 2019: 815-818 - [c38]Vladik Kreinovich, Martine Ceberio, Ricardo Alvarez:
How to Use Quantum Computing to Check Which Inputs Are Relevant: A Proof That Deutsch-Jozsa Algorithm Is, In Effect, the Only Possibility. SSCI 2019: 829-833 - [c37]Omeiza Olumoye, Glen Throneberry, Angel F. Garcia Contreras, Leobardo Valera, Abdessattar Abdelkefi, Martine Ceberio:
Solving Large Dynamical Systems by Constraint Sampling. WEA 2019: 3-15 - [e2]Ralph Baker Kearfott, Ildar Z. Batyrshin, Marek Z. Reformat, Martine Ceberio, Vladik Kreinovich:
Fuzzy Techniques: Theory and Applications - Proceedings of the 2019 Joint World Congress of the International Fuzzy Systems Association and the Annual Conference of the North American Fuzzy Information Processing Society IFSA/NAFIPS'2019 (Lafayette, Louisiana, USA, June 18-21, 2019). Advances in Intelligent Systems and Computing 1000, Springer 2019, ISBN 978-3-030-21919-2 [contents] - 2017
- [c36]Leobardo Valera, Angel F. Garcia Contreras, Martine Ceberio:
"On-the-fly" Parameter Identification for Dynamic Systems Control, Using Interval Computations and Reduced-Order Modeling. NAFIPS 2017: 293-299 - [c35]Leobardo Valera, Angel F. Garcia Contreras, Afshin Gholamy, Martine Ceberio, Horacio Florez:
Towards predictions of large dynamic systems' behavior using reduced-order modeling and interval computations. SMC 2017: 345-350 - 2016
- [c34]Martine Ceberio, Vladik Kreinovich:
Greetings from NAFIPS 2016 organizing committee chairs. NAFIPS 2016: 1 - [c33]Angel F. Garcia Contreras, Martine Ceberio:
Comparison of strategies for solving global optimization problems using speculation and interval computations. NAFIPS 2016: 1-6 - [c32]Leobardo Valera, Martine Ceberio:
Using Interval Constraint Solving Techniques to better understand and predict future behaviors of dynamic problems. NAFIPS 2016: 1-6 - [c31]Anthony Welte, Luc Jaulin, Martine Ceberio, Vladik Kreinovich:
Robust data processing in the presence of uncertainty and outliers: Case of localization problems. SSCI 2016: 1-7 - 2015
- [c30]Alberto Esquinca, Elsa Q. Villa, Elaine Hampton, Martine Ceberio, Luciene Wandermurem:
Latinas' resilience and persistence in computer science and engineering: Preliminary findings of a qualitative study examining identity and agency. FIE 2015: 1-4 - [c29]Salem Benferhat, Martine Ceberio, Vladik Kreinovich, Sylvain Lagrue, Karim Tabia:
On the Normalization of Interval-Based Possibility Distributions. FLAIRS 2015: 20-25 - [c28]Martine Ceberio, Leobardo Valera, Olga Kosheleva, Rodrigo Romero:
Model reduction: Why it is possible and how it can potentially help to control swarms of Unmanned Arial Vehicles (UAVs). NAFIPS/WConSC 2015: 1-6 - [c27]Martine Ceberio, Vladik Kreinovich, Hung T. Nguyen, Songsak Sriboonchitta, Rujira Ouncharoen:
What is the Right Context for an Engineering Problem: Finding Such a Context is NP-Hard. SSCI 2015: 1615-1620 - 2014
- [c26]Quentin Brefort, Luc Jaulin, Martine Ceberio, Vladik Kreinovich:
If we take into account that constraints are soft, then processing constraints becomes algorithmically solvable. CIES 2014: 1-10 - [c25]Stefano Bistarelli, Martine Ceberio, Joel A. Henderson, Francesco Santini:
Abstract argumentation frameworks to promote fairness and rationality in multi-experts multi-criteria decision making. ICTCS 2014: 247-257 - [p12]Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Simplicity Is Worse Than Theft: A Constraint-Based Explanation of a Seemingly Counter-Intuitive Russian Saying. Constraint Programming and Decision Making 2014: 9-13 - [p11]Martine Ceberio, Vladik Kreinovich:
Continuous If-Then Statements Are Computable. Constraint Programming and Decision Making 2014: 15-18 - [p10]Aline Jaimes, Craig Tweedy, Tanja Magoc, Vladik Kreinovich, Martine Ceberio:
Selecting the Best Location for a Meteorological Tower: A Case Study of Multi-objective Constraint Optimization. Constraint Programming and Decision Making 2014: 61-65 - [p9]Olga Kosheleva, Martine Ceberio, Vladik Kreinovich:
Why Tensors? Constraint Programming and Decision Making 2014: 75-78 - [p8]Olga Kosheleva, Martine Ceberio, Vladik Kreinovich:
Adding Constraints - A (Seemingly Counterintuitive but) Useful Heuristic in Solving Difficult Problems. Constraint Programming and Decision Making 2014: 79-83 - [p7]Vladik Kreinovich, Juan Ferret, Martine Ceberio:
Constraint-Related Reinterpretation of Fundamental Physical Equations Can Serve as a Built-In Regularization. Constraint Programming and Decision Making 2014: 91-95 - [p6]Paden Portillo, Martine Ceberio, Vladik Kreinovich:
Towards an Efficient Bisection of Ellipsoids. Constraint Programming and Decision Making 2014: 137-141 - [p5]Uram Anibal Sosa Aguirre, Martine Ceberio, Vladik Kreinovich:
Why Curvature in L-Curve: Combining Soft Constraints. Constraint Programming and Decision Making 2014: 175-179 - [p4]Karen Villaverde, Olga Kosheleva, Martine Ceberio:
Why Ellipsoid Constraints, Ellipsoid Clusters, and Riemannian Space-Time: Dvoretzky's Theorem Revisited. Constraint Programming and Decision Making 2014: 203-207 - [e1]Martine Ceberio, Vladik Kreinovich:
Constraint Programming and Decision Making. Studies in Computational Intelligence 539, Springer 2014, ISBN 978-3-319-04279-4 [contents] - 2013
- [c24]Xiaojing Wang, Martine Ceberio, Angel F. Garcia Contreras:
Towards fuzzy method for estimating prediction accuracy for discrete inputs, with application to predicting at-risk students. IFSA/NAFIPS 2013: 536-539 - [c23]Francisco Zapata, Ricardo Pineda, Martine Ceberio:
How to generate worst-case scenarios when testing already deployed systems against unexpected situations. IFSA/NAFIPS 2013: 617-622 - [p3]Christian Servin, Martine Ceberio, Aline Jaimes, Craig E. Tweedie, Vladik Kreinovich:
How to Describe and Propagate Uncertainty When Processing Time Series: Metrological and Computational Challenges, with Potential Applications to Environmental Studies. Time Series Analysis, Modeling and Applications 2013: 279-299 - 2012
- [c22]Xiaojing Wang, Angel F. Garcia Contreras, Martine Ceberio, Christian Del Hoyo, Luis C. Gutierrez:
A speculative algorithm to extract fuzzy measures from sample data. FUZZ-IEEE 2012: 1-8 - 2011
- [j11]Martine Ceberio, Vladik Kreinovich:
SCAN 2008 Guest editors preface. Reliab. Comput. 15(1) (2011) - [j10]Tanja Magoc, Martine Ceberio, François Modave:
Using Preference Constraints to Solve Multi-Criteria Decision Making Problems. Reliab. Comput. 15(3): 218-229 (2011) - [j9]Tanja Magoc, Xiaojing Wang, François Modave, Martine Ceberio:
Applications of Fuzzy Measures and Intervals in Finance. Reliab. Comput. 15(4): 300-311 (2011) - [c21]Martine Ceberio, Vladik Kreinovich:
No-Free-Lunch Result for Interval and Fuzzy Computing: When Bounds Are Unusually Good, Their Computation Is Unusually Slow. MICAI (2) 2011: 13-23 - [c20]Vladik Kreinovich, Christelle Jacob, Didier Dubois, Janette Cardoso, Martine Ceberio, Ildar Z. Batyrshin:
Estimating Probability of Failure of a Complex System Based on Inexact Information about Subsystems and Components, with Potential Applications to Aircraft Maintenance. MICAI (2) 2011: 70-81 - [c19]Jan Sliwka, Luc Jaulin, Martine Ceberio, Vladik Kreinovich:
Processing interval sensor data in the presence of outliers, with potential applications to localizing underwater robots. SMC 2011: 2330-2337 - 2010
- [c18]Aline Jaimes, Craig E. Tweedie, Tanja Magoc, Vladik Kreinovich, Martine Ceberio:
Multi-objective optimization under positivity constraints, with a meteorological example. FUZZ-IEEE 2010: 1-7 - [c17]Olga Kosheleva, Martine Ceberio:
Why polynomial formulas in soft computing, decision making, etc.? FUZZ-IEEE 2010: 1-5
2000 – 2009
- 2009
- [p2]Hung T. Nguyen, Vladik Kreinovich, François Modave, Martine Ceberio:
Fuzzy without Fuzzy: Why Fuzzy-Related Aggregation Techniques Are Often Better Even in Situations without True Fuzziness. Foundations of Computational Intelligence (2) 2009: 27-51 - [p1]Tanja Magoc, François Modave, Martine Ceberio, Vladik Kreinovich:
Computational Methods for Investment Portfolio: The Use of Fuzzy Measures and Constraint Programming for Risk Management. Foundations of Computational Intelligence (2) 2009: 133-173 - 2008
- [j8]Chandra Sekhar Pedamallu, Linet Özdamar, Martine Ceberio:
Efficient interval partitioning - Local search collaboration for constraint satisfaction. Comput. Oper. Res. 35(5): 1412-1435 (2008) - [c16]François Modave, Martine Ceberio, Vladik Kreinovich:
Choquet Integrals and OWA Criteria as a Natural (and Optimal) Next Step after Linear Aggregation: A New General Justification. MICAI 2008: 741-753 - [c15]Christian Servin, Martine Ceberio:
Cascade Vulnerability Problem Simulator Tool. MSV 2008: 227-231 - [c14]Yoonsik Cheon, Antonio Cortes, Gary T. Leavens, Martine Ceberio:
Integrating Random Testing with Constraints for Improved Efficiency and Diversity. SEKE 2008: 861-866 - [c13]Carlos Acosta, Martine Ceberio, Christian Servin:
A Constraint-Based Approach to Verification of Programs with Floating-Point Numbers. Software Engineering Research and Practice 2008: 232-237 - 2007
- [j7]Daniel Berleant, Martine Ceberio, Gang Xiang, Vladik Kreinovich:
Towards adding probabilities and correlations to interval computations. Int. J. Approx. Reason. 46(3): 499-510 (2007) - [j6]Gang Xiang, Martine Ceberio, Vladik Kreinovich:
Computing Population Variance and Entropy under Interval Uncertainty: Linear-Time Algorithms. Reliab. Comput. 13(6): 467-488 (2007) - [c12]Martine Ceberio, Vladik Kreinovich, Andrzej Pownuk, Barnabás Bede:
From Interval Computations to Constraint-Related Set Computations: Towards Faster Estimation of Statistics and ODEs Under Interval, p-Box, and Fuzzy Uncertainty. IFSA (1) 2007: 33-42 - 2006
- [j5]Vladik Kreinovich, Gang Xiang, Scott A. Starks, Luc Longpré, Martine Ceberio, Roberto Araiza, Jan Beck, Raj Kandathi, Asis Nayak, Roberto Torres, Janos G. Hajagos:
Towards Combining Probabilistic and Interval Uncertainty in Engineering Calculations: Algorithms for Computing Statistics under Interval Uncertainty, and Their Computational Complexity. Reliab. Comput. 12(6): 471-501 (2006) - [c11]Martine Ceberio, Vladik Kreinovich, Michel Rueher:
Editorial: track reliable computations and their applications. SAC 2006: 1633-1634 - [c10]Michael Orshansky, Wei-Shen Wang, Martine Ceberio, Gang Xiang:
Interval-based robust statistical techniques for non-negative convex functions, with application to timing analysis of computer chips. SAC 2006: 1645-1649 - 2005
- [j4]Martine Ceberio, Vladik Kreinovich, Michel Rueher:
Reliable Computations and Their Applications (RCA) Track. Reliab. Comput. 11(6): 499-503 (2005) - [c9]Martine Ceberio, Richard Coy:
Enhancement of Parameter Estimation using Flexible Constraints: an Application to Shock-response Study. AMCS 2005: 98-106 - [c8]Martine Ceberio, Hiroshi Hosobe, Ken Satoh:
Speculative Constraint Processing with Iterative Revision for Disjunctive Answers. CLIMA 2005: 340-357 - [c7]Martine Ceberio, François Modave, Xiaojing Wang:
Comparing Attacks: An Approach Based on Interval Computation and Fuzzy Integration. FUZZ-IEEE 2005: 897-902 - [c6]Martine Ceberio, Vladik Kreinovich, Michel Rueher:
Editorial: track reliable computations and their applications. SAC 2005: 1429-1430 - 2004
- [j3]Martine Ceberio, Vladik Kreinovich:
Greedy algorithms for optimizing multivariate Horner schemes. SIGSAM Bull. 38(1): 8-15 (2004) - [j2]Martine Ceberio, Vladik Kreinovich:
Fast Multiplication of Interval Matrices (Interval Version of Strassen's Algorithm). Reliab. Comput. 10(3): 241-243 (2004) - [c5]Martine Ceberio, François Modave:
Interval-Based Multicriteria Decision Making. AI&M 2004 - [c4]Martine Ceberio, Vladik Kreinovich, Lev Ginzburg:
On the Use of Intervals in Scientific Computing: What Is the Best Transition from Linear to Quadratic Approximation?. PARA 2004: 75-82 - 2002
- [j1]Martine Ceberio, Laurent Granvilliers:
Horner's Rule for Interval Evaluation Revisited. Computing 69(1): 51-81 (2002) - [c3]Martine Ceberio, Laurent Granvilliers:
Solving Nonlinear Equations by Abstraction, Gaussian Elimination, and Interval Methods. FroCoS 2002: 117-131 - 2000
- [c2]Martine Ceberio, Laurent Granvilliers:
Solving Nonlinear Systems by Constraint Inversion and Interval Arithmetic. AISC 2000: 127-141 - [c1]Martine Ceberio, Laurent Granvilliers:
Résolution de systèmes non linéaires par inversion des contraintes et analyse par intervalles. JFPLC 2000: 205-220
Coauthor Index
Angel F. Garcia Contreras
aka: Angel Fernando Garcia Contreras
aka: Angel Fernando Garcia Contreras
[j17] [c59] [c58] [c57] [c56] [c55] [c54] [p37] [p36] [p35] [p34] [p33] [p32] [p31] [p30] [p29] [p28] [p27] [p26] [p25] [p24] [p23] [p22] [e6] [e5] [j15] [j14] [e4] [j13] [c52] [j12] [c49] [c48] [c47] [c46] [c45] [c44] [p21] [p20] [p19] [p18] [p17] [p16] [p15] [p14] [p13] [e3] [c43] [c42] [c41] [c40] [c39] [c38] [e2] [c34] [c31] [c29] [c27] [c26] [p12] [p11] [p10] [p9] [p8] [p7] [p6] [p5] [e1] [p3] [j11] [c21] [c20] [c19] [c18] [p2] [p1] [c16] [j7] [j6] [c12] [j5] [c11] [j4] [c6] [j3] [j2] [c4]
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last updated on 2024-10-07 22:07 CEST by the dblp team
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